Processes and Systems Using and Producing Food Healthfulness Data Based on Linear Combinations of Nutrients

ABSTRACT

Processes for selecting and purchasing and/or consuming food are provided. In certain embodiments, healthfulness data representing a relative healthfulness of a candidate food is based on a linear combination of nutrient amounts present in a candidate food. Related processes for producing food energy data and for producing a food product are provided. Related processes and systems for supplying food energy data to a requester and supplying meal plan data to a consumer are also provided.

BENEFIT AND RELATED APPLICATIONS

This application claims the benefit of U.S. provisional patent application No. 61/092,981, filed Aug. 29, 2008, in the names of Karen Miller-Kovach, Ute Gerwig, Julia Peetz, Christine Jacobsohn, Wanema Frye, Stephanie Lyn Rost and Maria Kinirons. The present application is related to U.S. patent application Ser. No. ______, entitled Processes and Systems Based on Metabolic Conversion Efficiency (Attorney docket No. 26753.006); U.S. patent application Ser. No. ______, entitled Processes and Systems Based on Dietary Fiber as Energy (Attorney docket No. 26753.008); U.S. patent application Ser. No. ______, entitled Processes and Systems Using and Producing Food Healthfulness Data based on Food Metagroups (Attorney docket No. 26753.010); U.S. patent application Ser. No. ______, entitled Processes and Systems for Achieving and Assisting in Improved Nutrition (Attorney docket No. 26753.014); and U.S. patent application Ser. No. ______, entitled Processes and Systems for Achieving and Assisting in Improved Nutrition based on Food Energy Data and Relative Healthfulness Data (Attorney docket No. 26753.016), each of which is filed concurrently herewith and all of which are hereby incorporated herein by reference in their entireties.

FIELD OF THE INVENTION

Processes are provided for selecting and purchasing and/or consuming foods for achieving healthful nutrition, as well as processes for producing food products, and processes and systems for assisting with each of the foregoing.

BACKGROUND OF THE INVENTION

Weight Watchers International, Inc. is the world's leading provider of weight management services, operating globally through a network of Company-owned and franchise operations. Weight Watchers provides a wide range of products, publications and programs for those interested in weight loss and weight control. With over four decades of weight management experience, expertise and know-how, Weight Watchers has become one of the most recognized and trusted brand names among weight conscious consumers.

Years ago, Weight Watchers pioneered innovative and successful methods for weight control and systems for assisting consumers in practicing such methods. Such methods and systems are the subjects of U.S. Pat. No. 6,040,531; U.S. Pat. No. 6,436,036; U.S. Pat. No. 6,663,564; U.S. Pat. No. 6,878,885 and U.S. Pat. No. 7,361,143, each of which is incorporated herein by reference in its entirety. These methods assign values to food servings based on their calorie content, which is increased on the basis of fat content and decreased on the basis of dietary fiber content. This assignment is carried out using a proprietary formula developed by Weight Watchers scientists. The values for food servings consumed each day are summed and the consumer ensures that they do not exceed a predetermined maximum value. These methods afford a simple and effective weight control framework, especially for those who cannot devote substantial attention to their weight control efforts.

While consumers are striving to control their body weight, whether for the object of losing or gaining weight, or simply to maintain the weight they have, they are also eager to ensure that they are eating healthfully. Both government and private entities are attempting to implement measures to educate consumers so that they might chose and consume healthier foods. In the United States of America (US), food products are required to display lists of ingredients and provide additional information such as the content of each macronutrient, total calories and content of nutrients such as sodium and saturated fat that are particularly important to those with cardiovascular diseases.

The Food Standards Agency of the United Kingdom has implemented a food labeling system termed the “Traffic Light Labeling” system that encourages food manufacturers to label their foods in a standard fashion to enable consumers to compare one product against another by comparing the amounts of four different nutrients in each, including fat, saturated fat or “saturates”, sugar and salt, and, in some cases, calorie content. For each nutrient, and the calorie content (if displayed), a color code is provided to indicate whether the amount of that nutrient is “high” (red color code), “medium” (amber color code) or “low” (green color code). For those keeping track of one or more particular nutrients, such as sodium and saturated fat in the case of those with a cardiovascular condition, this labeling system can be quite effective. But for those trying to develop an overall sense of the healthfulness of each food product they are considering for purchase and/or consumption, a considerable amount of judgment may be necessary to determine whether to purchase or consume a particular food product.

Published PCT application WO 98/45766 to Sanchez proposes a food group nutritional value calculator that inputs data such as that displayed in following the Traffic Light Labeling system along with a consumer's selection of one of eight “food groups”. Based on the food group selection, the calculator carries out a corresponding decision-tree algorithm by comparing the input amounts of selected nutrients against standard values specific to each of the separate food groups. Based on one or more such comparisons, the food is classified as either “Excellent”, “Very Good”, “Good” or “Avoid”.

DISCLOSURE

FIGS. 1 through 9 are tables of data used in processes disclosed herein for producing data representing the relative healthfulness of various foods;

FIG. 10 is a flow chart illustrating certain disclosed processes for selecting and ingesting foods based on their relative healthfulness;

FIG. 11 is a flow chart illustrating certain disclosed processes for selecting and purchasing foods based on their relative healthfulness;

FIG. 12 illustrates certain embodiments of data processing systems useful in the processes disclosed herein;

FIG. 13 illustrates certain embodiments of client/server systems useful in the processes disclosed herein;

FIGS. 14A through 14D illustrate exemplary images for use in conveying energy content data and nutritional characteristic data of foods; and

FIG. 15 is a flow chart illustrating certain disclosed processes for producing a food product having relative healthfulness data associated therewith.

For this application the following terms and definitions shall apply:

The term “healthfulness” as used herein to refer to a food or type of food refers to either or both of (a) the presence and/or amount of one or more nutrients therein which can be detrimental to a consumer's health, and (b) a characteristic thereof which tends to promote healthful nutrition, whether evaluated on a relative or absolute basis.

The term “energy density” as used herein to refer to a food or type of food refers to an evaluation thereof that reflects its energy content relative to an amount thereof, whether expressed on an absolute basis or relative to the energy density of one or more other foods or types of foods.

The term “data” as used herein means any indicia, signals, marks, symbols, domains, symbol sets, representations, and any other physical form or forms representing information, whether permanent or temporary, whether visible, audible, acoustic, electric, magnetic, electromagnetic or otherwise manifested. The term “data” as used to represent predetermined information in one physical form shall be deemed to encompass any and all representations of corresponding information in a different physical form or forms.

The term “presentation data” as used herein means data to be presented to a user in any perceptible form, including but not limited to, visual form and aural form. Examples of presentation data include data displayed on a visual presentation device, such as a monitor, and data printed on paper.

The term “presentation device” as used herein means a device or devices capable of presenting data to a user in any perceptible form.

The term “database” as used herein means an organized body of related data, regardless of the manner in which the data or the organized body thereof is represented. For example, the organized body of related data may be in the form of one or more of a table, a map, a grid, a packet, a datagram, a frame, a file, an e-mail, a message, a document, a list or in any other form.

The term “image dataset” as used herein means a database suitable for use as presentation data or for use in producing presentation data.

The term “auxiliary image feature” as used herein means one or more of the color, brightness, shading, shape or texture of an image.

The term “network” as used herein includes both networks and internetworks of all kinds, including the Internet, and is not limited to any particular network or inter-network. For example, “network” includes those that are implemented using wired links, wireless links or any combination of wired and wireless links.

The terms “first”, “second”, “primary” and “secondary” are used to distinguish one element, set, data, object, step, process, activity or thing from another, and are not used to designate relative position or arrangement in time, unless otherwise stated explicitly.

The terms “coupled”, “coupled to”, and “coupled with” as used herein each mean a relationship between or among two or more devices, apparatus, files, circuits, elements, functions, operations, processes, programs, media, components, networks, systems, subsystems, and/or means, constituting any one or more of (a) a connection, whether direct or through one or more other devices, apparatus, files, circuits, elements, functions, operations, processes, programs, media, components, networks, systems, subsystems, or means, (b) a communication relationship, whether direct or through one or more other devices, apparatus, files, circuits, elements, functions, operations, processes, programs, media, components, networks, systems, subsystems, or means, and/or (c) a functional relationship in which the operation of any one or more devices, apparatus, files, circuits, elements, functions, operations, processes, programs, media, components, networks, systems, subsystems, or means depends, in whole or in part, on the operation of any one or more others thereof.

The terms “communicate,” “communicating” and “communication” as used herein include both conveying data from a source to a destination, and delivering data to a communication medium, system, channel, network, device, wire, cable, fiber, circuit and/or link to be conveyed to a destination. The term “communications” as used herein includes one or more of a communication medium, system, channel, network, device, wire, cable, fiber, circuit and link.

The term “processor” as used herein means processing devices, apparatus, programs, circuits, components, systems and subsystems, whether implemented in hardware, software or both, and whether or not programmable. The term “processor” as used herein includes, but is not limited to one or more computers, hardwired circuits, neural networks, signal modifying devices and systems, devices and machines for controlling systems, central processing units, programmable devices and systems, field programmable gate arrays, application specific integrated circuits, systems on a chip, systems comprised of discrete elements and/or circuits, state machines, virtual machines, data processors, processing facilities and combinations of any of the foregoing.

The term “data processing system” as used herein means a system implemented at least in part by hardware and comprising a data input device, a data output device and a processor coupled with the data input device to receive data therefrom and coupled with the output device to provide processed data thereto.

The terms “obtain”, “obtained” and “obtaining”, as used with respect to a processor or data processing system mean (a) producing data by processing data, (b) retrieving data from storage, or (c) requesting and receiving data from a further data processing system.

The terms “storage” and “data storage” as used herein mean one or more data storage devices, apparatus, programs, circuits, components, systems, subsystems, locations and storage media serving to retain data, whether on a temporary or permanent basis, and to provide such retained data.

The terms “food serving identification data” and “food serving ID data” as used herein mean data of any kind that is sufficient to identify a food and to convey an amount thereof, whether by mass, weight, volume, or size, or by reference to a standard or otherwise defined food serving, or by amounts of constituents thereof. The terms “amount” and “amounts” as used herein refer both to absolute and relative measures.

The terms “food identification data” and “food ID data” as used herein mean data of any kind that is sufficient to identify a food, whether or not such data conveys an amount thereof.

A process for selecting and consuming and/or purchasing food based on the healthfulness of the food relative to one or more other foods comprises, for each of a plurality of candidate foods, obtaining respective healthfulness data representing a relative healthfulness of each of the candidate foods, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; selecting at least one of the candidate foods from the plurality of candidate foods based on its respective healthfulness data; and at least one of ingesting the at least one of the candidate foods and purchasing the at least one of the candidate foods.

In certain embodiments, the healthfulness data of at least one of the candidate foods is based on its energy density. In certain embodiments, the healthfulness data for at least two of the candidate foods is based on a respectively different linear combination of selected nutrient amounts therein. In certain embodiments, each of the candidate foods is classified in a respective one of a plurality of food groups and the healthfulness data of each of the candidate foods is based on a respective linear combination of selected nutrients therein corresponding to the food group thereof, the respective linear combinations of selected nutrients of at least two of the food groups being different. In certain embodiments, meal plan data comprising data identifying food servings to be ingested over a given period is obtained based on the healthfulness data, and the at least one of the candidate foods is selected based on the meal plan data.

A process for producing relative healthfulness data for a selected food comprises, in a data processing system, receiving a plurality of nutrient data representing amounts of each of a plurality of nutrients in the selected food; and in the data processing system, obtaining relative healthfulness data for the selected food based on a linear combination of the plurality of nutrient data.

In certain embodiments, the relative healthfulness data is stored in storage. In certain ones of such embodiments, the relative healthfulness data is stored in a database of existing relative healthfulness data in order to update it.

A process for providing data to a data requester representing healthfulness of a predetermined food relative to one or more other foods comprises receiving in a data processing system request data provided by the data requestor requesting relative healthfulness data for a selected food; using a processor of the data processing system, obtaining relative healthfulness data representing a relative healthfulness of the selected food, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; and at least one of (a) communicating the relative healthfulness data to a device for presentation to the consumer, and (b) presenting the relative healthfulness data to the consumer via a presentation device of the data processing system.

A system for providing data to a data requester representing healthfulness of a selected food relative to one or more other foods comprises an input operative to receive request data provided by the data requestor requesting healthfulness data for a selected food; a processor coupled with the input to receive the request data provided by the data requester and configured to obtain relative healthfulness data representing a relative healthfulness of the selected food, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; and at least one of (a) communications coupled with the processor to receive the relative healthfulness data therefrom and to communicate the relative healthfulness data to a device for presentation to the consumer, and (b) a presentation device coupled with the processor to receive the relative healthfulness data and operative to present the relative healthfulness data to the consumer.

A process for providing meal plan data to a consumer, comprises receiving request data in a data processing system representing a request for a meal plan from a consumer; in response to the request, obtaining meal plan data representing a plurality of predetermined food servings to be consumed by the consumer during a predetermined period based on relative healthfulness data for respective predetermined food servings, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; and at least one of (a) communicating the meal plan data to a device for presentation to the data requester, and (b) presenting the meal plan data to the data requester via a presentation device of the data processing system.

A system for providing meal plan data to a consumer comprises an input operative to receive request data representing a request for a meal plan from the consumer; a processor coupled with the input to receive the request data and configured to obtain meal plan data representing a plurality of predetermined food servings to be consumed by the consumer during a predetermined period based on relative healthfulness data for each of a plurality of predetermined food servings, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; and at least one of (a) communications coupled with the processor to receive the meal plan data therefrom and to communicate the meal plan data to a device for presentation to the consumer, and (b) a presentation device coupled with the processor to receive the meal plan data and operative to present the meal plan data to the consumer.

In certain embodiments, the processor is configured to obtain the relative healthfulness data, and to obtain the meal plan data based on the relative healthfulness data

A process for producing a food product having relative healthfulness data associated therewith comprises obtaining a food product, supplying at least one of food identification data and food nutrient data of the food product; obtaining healthfulness data representing a relative healthfulness of the food product based on its at least one of food identification data and food nutrient data, the healthfulness data for the food product being based on a linear combination of selected nutrient amounts present therein; and associating the healthfulness data with the food product.

In certain embodiments, the healthfulness data is associated with the food product by including the healthfulness data on a substrate associated with the food product. In certain ones of such embodiments, the substrate comprises packaging of the food product. In certain ones of such embodiments, the substrate comprises a label accompanying the food product.

In certain embodiments, the relative healthfulness data is determined in a manner that depends on a particular food group of the selected food. In certain ones of such embodiments, the healthfulness data is determined in a first, common manner for foods within a first metagroup comprising the following groups: beans, dry & legumes; and oils. The healthfulness data (HD) for these groups is obtained based on a linear combination of fat content data, saturated fat content data, sugar content data and sodium content data for the food. In one such embodiment, the healthfulness data is produced by processing fat content data (F_data), saturated fat content data (SF_data), sugar content data (S_data) and sodium content data (NA_data), as follows, wherein such data is determined as explained hereinbelow:

HD=[(2×(SF_data+F_data)+S_data+NA_data]/4/kcal_(—) DV  (1)

where kcal_DV is determined as explained hereinbelow. The table of FIG. 1 illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (1) and a comparison thereof against the exemplary comparison data included therein. These values may be varied from place to place, from culture to culture and from time to time, to provide a fair comparison of available foods and food products.

It will also be appreciated that the food groups and metagroups, and the corresponding procedures and comparison values, as disclosed herein may be varied based on variations in the foods and food products available from place to place, culture to culture and over time. They may also vary to accommodate the needs and desires of certain segments of the population, such as those with special needs (for example, diabetic patients and those living in extreme climates) and those with particular healthfulness goals (which can vary, for example, with physical activity level). Such groups, metagroups, procedures, and comparison values are selected based on the similarities of foods and the manner in which related foods vary in the amounts and types of nutrients that tend to affect their healthfulness.

The value selected for kcal_DV is selected to represent a daily calorie value that depends on the purposes or needs of the class of consumers for whom the relative healthfulness data is provided. For example, if this class encompasses individuals desiring to loose body weight, the value of kcal_DV is selected as a daily calorie target to ensure weight loss, such as 1500 kcal. However, this value may differ from culture to culture and from country to country. For example, the energy needs of those living in China are generally lower than those living in the United States, so that kcal_DV may be selected at a lower value for Chinese individuals trying to reduce body weight than for those living in the United States. As a further example, if the class of consumers for whom the relative healthfulness data is provided encompasses athletes attempting to maintain body weight during training, kcal_DV may be set at a much higher level than 1500 kcal. For most purposes, kcal_DV may be selected in a range from 1000 kcal to 3000 kcal.

The value of SF_data is determined relative to a recommended or otherwise standardized limit on an amount or proportion of saturated fat to be included in a person's daily food intake. The. recommended or otherwise standardized amount or proportion of saturated fat to be consumed daily is based on the person's presumed total food energy intake daily, and a proportion thereof represented by saturated fat. In certain embodiments, for consumers desiring to lose body weight, as explained hereinabove, a total food energy intake of 1500 kcal is assumed (although the amount may vary in other embodiments). If, for example, a maximum desirable percentage of saturated fat consumed as a proportion of total daily energy intake is assumed to be seven percent, then the total number of calories in saturated fat that the person consumes daily on such a diet should be limited to about 105 kcal (of a total of 1500 kcal). Since fat contains about nine kcal per gram, the person's daily consumption of saturated fat in this example should be limited to about twelve grams. However, the recommended or standardized limit on the proportion or amount of saturated fat to be consumed may vary from one class of consumer to another, as well as from country to country and from culture to culture. SF_data is determined by comparison to such a standard. In this example, therefore, SF_data is determined as the ratio of (a) the mass of saturated fat in a standard amount of the food under evaluation, to (b) twelve grams. While a different procedure or other amounts or proportions may be employed in other embodiments to evaluate the saturated fat content of a food, it is desired to determine SF_data in a manner that is reasonably comparable to the ways in which F_data, S_data and NA_data are determined.

Similarly to SF_data, the value of F_data is determined relative to a recommended or otherwise standardized limit on the amount or proportion of total fat to be included in a person's daily food intake. In those embodiments in which it is presumed that a person consumes 1500 kcal daily and a recommended proportion or limit of thirty percent of energy consumption in the form of fat is adopted, this translates to fifty grams of total fat on a daily basis. In this example, therefore, and in particular for comparability to SF_data, F_data is determined as the ratio of (a) the mass of total fat in a standard amount of the food under evaluation, to (b) fifty grams. Of course, a different procedure or other amounts or proportions may be employed in other embodiments to evaluate the total fat content of a food.

In a similar manner, the value of S_data is determined relative to a recommended or otherwise standardized limit on the amount or proportion of sugar to be included in a person's daily food intake. In those embodiments in which it is presumed that a person consumes 1500 kcal daily and a recommended proportion or limit of ten percent of food energy intake in the form of sugar is adopted, this translates to thirty eight grams of sugar on a daily basis (at four kcal per gram of sugar). In this example, therefore, and in particular for comparability to SF_data and F_data, S_data is determined as the ratio of (a) the mass of sugar in a standard amount of the food under evaluation, to (b) thirty eight grams. Of course, a different procedure or other amounts or proportions may be employed in other embodiments to evaluate the sugar content of a food.

In a manner similar to those described above, the value of NA_data is determined relative to a recommended or otherwise standardized limit on the amount or proportion of sodium to be included in a person's daily food intake. In those embodiments in which a recommended limit of 2400 mg of sodium consumed daily is adopted, NA_data is determined as the ratio of (a) the mass of sodium in a standard amount of the food under evaluation, to (b) 2400 mg. Of course, a different procedure or other amounts or proportions may be employed in other embodiments to evaluate the sodium content of a food.

In such embodiments, the healthfulness data is determined in a second, common manner for foods within a second metagroup comprising the following groups: beef (cooked), cookies, cream & creamers, eggs, frankfurters, game (raw), game (cooked), lamb (cooked), luncheon meats, pizza, pork (raw), pork (cooked), sausage, snacks—pretzels, veal (raw) and veal (cooked). The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's fat content data, saturated fat content data, sugar content data, sodium content data and energy density data. In one such embodiment, the healthfulness data is produced by processing F_data, SF_data, S_data, NA_data and ED_data of the food, as follows, wherein F_data, SF_data, S_data and NA_data are obtained as explained hereinabove:

HD=ED_data+([(2×SF_data)+(2×F_data)+NA_data+S_data]×100/M_serving),  (2)

where M_serving is the mass or weight of a standard serving of the food. In this particular embodiment, ED_data is obtained as the energy content of the food (in kcal) divided by its mass (in grams). The tables of FIGS. 1A and 1B illustrate how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (2) and a comparison thereof against the exemplary comparison data included therein.

In such embodiments, the healthfulness data is determined in a third, common manner for foods within a third metagroup comprising the following groups: beverages; alcoholic beverages; sweet spreads—jams, syrups, toppings & nut butters. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's fat content data, saturated fat content data, sugar content data, sodium content data and energy density data. In one such embodiment, the healthfulness data is produced by processing F_data, SF_data, S_data, NA_data, ED_data and M_serving, as follows:

HD=(ED_data÷3)+[(2×SF_data)+(2×F_data)+(2×S_data)+NA_data]÷M_serving.  (3)

The table of FIG. 2 illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (3) and a comparison thereof against the exemplary comparison data included therein.

In such embodiments, the healthfulness data is determined in a fourth, common manner for foods within a fourth metagroup comprising the following groups: cheese, dairy & non-dairy, hard; and cheese, cottage & cream. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's fat content data, saturated fat content data, sugar content data, sodium content data and energy density data. In one such embodiment, the healthfulness data is produced by processing F_data, SF_data, S_data, NA_data, ED_data and M_serving, as follows:

HD=ED_data+[(4×SF_data)+(4×F_data)+S_data+NA_data]×100/M_serving.  (4)

The table of FIG. 2A illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (4) and a comparison thereof against the exemplary comparison data included in FIG. 2A.

In such embodiments, the healthfulness data is determined in a fifth, common manner for foods within a fifth metagroup comprising the following groups: breads; bagels; tortillas, wraps; breakfast—pancakes, waffles, pastries; and vegetable dishes The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's fat content data, saturated fat content data, sugar content data, sodium content data and energy density data. In one such embodiment, the healthfulness data is produced by processing F_data, SF_data, S_data, NA_data, ED_data and M_serving, as follows:

HD=ED_data+[(2×SF_data)+F_data+S_data+(2×NA_data)−DF_data]×100/M_serving.  (5)

The value of DF_data is determined relative to a recommended or otherwise standardized minimum amount or proportion of dietary fiber to be included in a person's daily food intake. One such recommendation is that a minimum of ten grams of dietary fiber be consumed by a person for every 1000 kcal consumed daily. In those embodiments in which it is presumed that a person consumes 1500 kcal daily, this translates to a recommended minimum of fifteen grams of dietary fiber on a daily basis. Of course, a different procedure or other amounts or proportions may be employed in other embodiments to evaluate the recommended amount of dietary fiber to be consumed on a periodic basis. In this particular example, the value of DF_data is obtained as the ratio of the mass of dietary fiber in a standard serving of then food, to fifteen grams.

The table of FIG. 3 illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (5) and a comparison thereof against the exemplary comparison data included in FIG. 3.

In such embodiments, the healthfulness data is determined in a sixth, common manner for foods within a sixth metagroup comprising the following groups: grains & pasta, cooked; and grains & pasta, uncooked. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's fat content data, saturated fat content data, sugar content data, sodium content data, energy density data and dietary fiber content data. In one such embodiment, the healthfulness data is produced by processing F_data, SF_data, S_data, NA_data, ED_data and DF_data, as follows:

HD=(ED_data/3)+[([SF_data+F_data+(2×S_data)+(2×NA_data)]/4)−DF_data]×100/M_serving.  (6)

The table of FIG. 3A illustrates how the foods of the groups in the sixth metagroup are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (6) and a comparison thereof against the exemplary comparison data included in FIG. 3A.

In such embodiments, the healthfulness data is determined in a seventh, common manner for foods within a seventh metagroup comprising the following groups: breakfast cereals, hot, cooked; breakfast cereals, hot, uncooked; and fruit salads. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's saturated fat content data, fat content data, sugar content data, sodium content data and energy density data. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=ED_data+[SF_data+(2×F_data)+(2×S_data)+(2×NA_data]×100/M_serving.  (7)

The table of FIG. 4 illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (7) and a comparison thereof against the exemplary comparison data included in FIG. 4.

In such embodiments, the healthfulness data is determined in an eighth, common manner for foods within an eighth metagroup comprising the following groups: bars; cakes and pastries; and candy. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's fat content data, saturated fat content data, sodium content data, energy density data and sugar content data. In one such embodiment, the healthfulness data is produced by processing F_data, SF_data, NA_data, ED_data and S_data, as follows:

HD=ED_data+[(2×SF_data)+F_data+(2×S_data)+(2×NA_data)]×100/M_serving.  (8)

The table of FIG. 5 illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (8) and a comparison thereof against the exemplary comparison data included in FIG. 5.

In such embodiments, the healthfulness data is determined in a ninth, common manner for foods within a ninth metagroup comprising the following groups: dips; dressings; gravies; sauces; soups, condensed; soups, RTE; and spreads (other than sweet). The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's fat content data, saturated fat content data, sodium content data, sugar content data and energy density data. In one such embodiment, the healthfulness data is produced by processing F_data, SF_data, S_data, NA_data, and ED_data, as follows:

HD=ED_data+[(2×SF_data)+F_data+S_data+(2×NA_data)]×100/M_serving.  (9)

The table of FIG. 6 illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (9) and a comparison thereof against the exemplary comparison data included in FIG. 6.

In such embodiments, the healthfulness data is determined in a tenth, common manner for foods within a tenth metagroup comprising the following groups: beans, dry & legumes dishes; beef dishes; breakfast mixed dishes; cheese dishes; chili, stew; egg dishes; fish & shellfish dishes; lamb dishes; pasta dishes; pasta, cooked; pork dishes; poultry dishes; rice & grains dishes; salads, main course; salads, side; sandwiches; veal dishes and vegetarian meat substitutes. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's fat content data, saturated fat content data, sodium content data, sugar content data and energy density data. In one such embodiment, the healthfulness data is produced by processing F_data, SF_data, NA_data, S_data and ED_data, as follows:

HD=ED_data+[(2×SF_data)+(2×F_data)+S_data+(2×NA_data)]×100/M_serving.  (10)

The tables of FIGS. 7 and 7A illustrate how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (10) and a comparison thereof against the exemplary comparison data included in FIGS. 7 and 7A.

In such embodiments, the healthfulness data is determined in an eleventh, common manner for foods within an eleventh metagroup comprising the following groups: fruit—fresh, frozen & dried; and fruit & vegetable juices. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's sodium content data, sugar content data, saturated fat content data, fat content data and energy density data. In one such embodiment, the healthfulness data is produced by processing NA_data, S_data, SF_data, F_data and ED_data, as follows:

HD=ED_data+[(2×S_data)+NA_data+SF_data+F_data]×100/M_serving.  (11)

The table of FIG. 8 illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (11) and a comparison thereof against the exemplary comparison data included in FIG. 8.

In such embodiments, the healthfulness data is determined in a twelfth, common manner for foods within a twelfth metagroup comprising the following groups: vegetables, raw; and vegetables, cooked. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's sodium content data, sugar content data, saturated fat content data, fat content data and energy density data. In one such embodiment, the healthfulness data is produced by processing NA_data, S_data, SF_data, F_data and ED_data, as follows:

HD=ED_data+[S_data+(1.5×NA_data)+(5×SF_data)+(5×F_data)]×100/M_serving.  (12)

The table of FIG. 8A illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (12) and a comparison thereof against the exemplary comparison data included in FIG. 8A.

In such embodiments, the healthfulness data is determined in a thirteenth, common manner for foods within a thirteenth metagroup comprising the following groups: gelatin, puddings; ice cream desserts; ice cream novelties; ice cream, sherbet, sorbet; sweet pies; and sweets—honey, sugar, syrup, toppings. The healthfulness data (HD) for these groups is obtained based on a linear combination of the food's sodium content data, fat content data, saturated fat content data, sugar content data, and energy density data. In one such embodiment, the healthfulness data is produced by processing NA_data, F_data, SF_data, S_data, and ED_data, as follows:

HD=ED_data+[(2×SF_data)+F_data+NA_data+(2×S_data)]×100/M_serving.  (13)

The table of FIG. 9 illustrates how the foods in these groups are ranked according to their healthfulness based on their respective healthfulness data produced in accordance with the process represented by equation (13) and a comparison thereof against the exemplary comparison data included in FIG. 9.

In such embodiments, the healthfulness data is determined in a fourteenth, common manner for foods within the following group: breakfast cereals, RTE. The healthfulness data (HD) for this group is obtained based on the saturated fat content data of the food, as well as its fat content data, sugar content data, sodium content data, dietary fiber content data and energy density data. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data, S_data, NA_data, DF_data and ED_data, as follows:

HD=(ED_data/3)+[(2×S_data)+SF_data+F_data+NA_data−DF_data]×100/M_serving.  (14)

For this group, the most healthful foods have an HD value less than or equal to −0.36, while less healthful foods have an HD value greater than −0.36 and less than or equal to 1.66, even less healthful foods have an HD value greater than 1.66 and less than or equal to 2.91 and the most unhealthful foods have an HD value greater than 2.91.

In such embodiments, the healthfulness data is determined in a fifteenth, common manner for foods within an fifteenth metagroup comprising the following group: coffee/tea drinks with milk. The healthfulness data (HD) for this group is obtained based on the saturated fat content data, the fat content data, the sodium content data and the sugar content data of the food. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data, S_data and NA_data, as follows:

HD=([(2×SF_data)+(2×F_data)+(2×S_data)+NA_data]/4)/kcal_DV.  (15)

For this group, the most healthful foods have an HD value less than or equal to 3.25, while relatively less healthful foods have an HD value greater that 3.25 and less than or equal to 3.471, even less healthful foods have an HD value greater than 3.471 and less than or equal to 4.18 and the least healthful foods have an HD value greater than 4.18.

In such embodiments, the healthfulness data is determined in a sixteenth, common manner for foods within the following group: crackers. The healthfulness data (HD) for this group is obtained based on the saturated fat content data, the fat content data, the sugar content data, the sodium content data and the energy density data of the food. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=(ED_data/3)+[(2×SF_data)+F_data+S_data+(2×NA_data)]×100/M_serving.  (16)

For this group, none of the foods are graded in the most healthful foods category, while relatively less healthful foods have an HD less than or equal to 1.805, even less healthful foods have an HD value greater than 1.805 and less than or equal to 3.2, and the least healthful foods have an HD value greater than 3.2.

In such embodiments, the healthfulness data is determined in a seventeenth, common manner for foods within the following group: fish, cooked. The healthfulness data (HD) for this group is obtained based on the saturated fat content data, the fat content data, the sugar content data, the sodium content data and the energy density data of the food. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=ED_data+[(4×SF_data)+(4×F_data)+S_data+(2×NA_data)]×100/M_serving.  (17)

For this group, the most healthful foods have an HD value less than or equal to 3.2, while relatively less healthful foods have an HD value greater that 3.2 and less than or equal to 4.7, even less healthful foods have an HD value greater than 4.7 and less than or equal to 6.6, and the least healthful foods have an HD value greater than 6.6.

In such embodiments, the healthfulness data is determined in a eighteenth, common manner for foods within the following group: fruit, canned. The healthfulness data (HD) for this group is obtained based on the saturated fat content data, the fat content data, the sugar content data, the sodium content data and the energy density data of the food. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=ED_data+[(2×SF_data)+(2×F_data)+(4×S_data)+(2×NA_data)]×100/M_serving.  (18)

For this group, the most healthful foods have an HD value less than or equal to 1.56, while relatively less healthful foods have an HD value greater that 1.56 and less than or equal to 1.93, even less healthful foods have an HD value greater than 1.93 and less than or equal to 3.27, and the least healthful foods have an HD value greater than 3.27.

In such embodiments, the healthfulness data is determined in a nineteenth, common manner for foods within the following group: nuts, nut butters. The healthfulness data (HD) for this group is obtained based on the saturated fat content data, the fat content data, the sugar content data, the sodium content data and the energy density data of the food. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data, S_data, NA_data and ED_data, as follows:

HD=(ED_data/3)+[(2×SF_data)+F_data+S_data+NA_data]×100/M_serving.  (19)

For this group, none of the foods are graded within the most healthful foods category, while relatively less healthful foods have an HD value less than or equal to 1.5, even less healthful foods have an HD value greater than 1.5 and less than or equal to 5.6, and the least healthful foods have an HD value greater than 5.6.

In such embodiments, the healthfulness data is determined in a twentieth, common manner for foods within the following group: snacks, other. The healthfulness data (HD) for this group is obtained based on the saturated fat content data, the fat content data and the energy density data of the food. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data and ED_data, as follows:

HD=ED_data+[SF_data+F_data]×100/M_serving.  (20)

For this group, none of the foods are graded within the most healthful foods category or in the relatively less healthful foods category, while even less healthful foods have an HD value less than or equal to 5.491, and the least healthful foods have an HD value greater than 5.491.

In such embodiments, the healthfulness data is determined in a twenty-first, common manner for foods within the following group: snacks—popcorn. The healthfulness data (HD) for this group is obtained based on the saturated fat content data of the food, as well as its fat content data, sugar content data, sodium content data, dietary fiber content data and energy density data. In one such embodiment, the healthfulness data is produced by processing SF_data, F_data, S_data, NA_data, DF_data and ED_data, as follows:

HD=ED_data+[(2×S_data)+SF_data+F_data+NA_data−DF_data]×100/M_serving.  (21)

For this group, the most healthful foods have an HD value less than or equal to 3.02, while less healthful foods have an HD value greater than 3.02 and less than or equal to 4.0, even less healthful foods have an HD value greater than 4.0 and less than or equal to 6.3 and the most unhealthful foods have an HD value greater than 6.3.

In certain embodiments, methods are provided for selecting and ingesting foods in a way that enables the consumer to simplify the task of evaluating the relative healthfulness of a candidate food serving. With reference to FIG. 10, a consumer considers ingesting a candidate food serving and supplies 210 data representing its identity and/or its nutrient content and a predetermined group including the candidate food serving. In order to evaluate the desirability of ingesting the candidate food serving, the consumer obtains 220 relative healthfulness data for the candidate food serving based on at least one of the data representing its (1) identity and (2) its nutrient content and group classification. Such relative healthfulness is determined as disclosed hereinabove. In certain advantageous embodiments, such relative healthfulness is represented by distinctly different and suggestive colors and/or shapes, for example: a green star to represent those foods that provided the greatest satiety for minimal kcal as well as a nutritional profile which most closely complements public health guidelines; a blue triangle to represent foods with a nutritional profile that is not as closely aligned with public health recommendations but does have satiety and nutritional virtues; a pink square to represent foods that provide minimal satiety or nutritional value to overall intake but are likely to enhance the tastefulness or convenience of eating; and a white circle to represent foods that, while not making much of a contribution to overall nutrition or feelings of satiety, provide pleasure and can be part of a healthy eating plan when consumed in moderation. In certain embodiments, the consumer obtains the relative healthfulness data in the form of meal plan data obtained, for example, as disclosed hereinbelow.

Based on the relative healthfulness data thus obtained, the consumer determines whether to accept or reject 230 the candidate food serving for consumption. For example, the consumer may wish to consume a snack food and must decide between a bag of fried corn chips and a bag of popcorn. He or she obtains their relative healthfulness data using one of the processes disclosed hereinabove, and decides 240 to consume the popcorn because its healthfulness relative to the fried corn chips is more favorable than that of the fried corn chips. Thus, if the consumer decides 230 to reject a candidate food serving, the process returns to 210 to be repeated when the consumer again considers a candidate food serving for ingestion. If the consumer decides to ingest the candidate food serving, the consumer ingests 240 the candidate food serving and the process returns to 210 to be repeated when the consumer again considers a candidate food serving for ingestion. Where the consumer considers two candidate food servings, and accepts one to be ingested and rejects the other, in effect the process as illustrated in FIG. 10 is carried out twice, once for the candidate food serving accepted by the consumer and again for the rejected candidate food serving.

A method of selecting and purchasing food for consumption utilizing the relative healthfulness data is illustrated in FIG. 11. When a consumer considers whether to purchase a given food offered for sale, the consumer supplies 250 data representing its identity and/or its nutrient content and a predetermined group including the food offered for sale. In order to evaluate the desirability of purchasing the food, the consumer obtains 260 relative healthfulness data for the food based on at least one of the data representing its (1) identity and (2) its nutrient content and group classification. The food may be a packaged food, such as a Weight Watchers® packaged food that displays an image on its packaging representing the relative healthfulness of the product offered for sale. Instead it may be a packaged food that does not display such an image, so that the consumer inputs an identification of the packaged food, or else its classification in a respective predetermined food group and nutrient content, in a device such as a PDA or cellular telephone to obtain a display of the relative healthfulness data, as disclose more fully hereinbelow. It might also be a food such as produce that is unpackaged and the consumer may obtain the relative healthfulness data in the same manner as for the packaged food lacking the image representing same. In certain embodiments, the consumer obtains the relative healthfulness data in the form of meal plan data obtained, for example, as disclosed hereinbelow.

Based on the relative healthfulness data, the consumer determines whether to accept or reject 270 the food for purchase. For example, the consumer may wish to purchase cookies and wishes to decide between two competing brands of the same kind of cookie. The relative healthfulness data provides a simple and straightforward means of making this decision.

When the consumer has selected all of the foods to be purchased 280, he or she then purchases the selected foods 290 and delivers or has them delivered 296 to his/her household for consumption.

With reference to FIG. 12 a data processing system 40 illustrated therein is useful in certain embodiments for carrying out the processes of FIGS. 13 and 14. The data processing system 40 comprises a processor 44, a storage 50 coupled with the processor 44, an input 56 coupled with processor 44, a presentation device 60 coupled with processor 44 and communications 64 coupled with processor 44.

Where system 40 is implemented as a PDA, laptop computer, desktop computer or cellular telephone, in certain ones of such embodiments the input 56 comprises one or more of a keypad, a keyboard, a point-and-click device (such as a mouse), a touchscreen, a microphone, switch(es), a removable storage or the like, and presentation device 60 comprises an LCD display, a plasma display, a CRT display, a printer, lights, LED's or the like.

In certain ones of such embodiments, storage 50 stores data identifying the predetermined food groups as well as instructions and comparison data for carrying out the processes necessary to produce the relative healthfulness data as summarized in equations (1) through (21) hereinabove. Using input 56, the consumer inputs data identifying the food to be consumed or food offered for sale or an identification of its predetermined food group, and processor 44 retrieves appropriate instructions from storage 50 for carrying out the respective process for the identified food group. Storage 50 stores data associating food identity data with the corresponding food groups, so that when the consumer inputs food identification data, processor 44 accesses such data to identify its food group and then retrieves the appropriate processing instructions based thereon. Processor 44 then prompts the consumer, via presentation device 60, to enter the relevant ones of F_data, SF_data, DF_data, S_data, NA_data, M_serving, kcal DV, DD, and ED_data for a food to be purchased or candidate food serving depending on the process to be carried out. Processor 44 then processes the input data according to one of equations (1) through (21) to produce a result for the identified food, accesses appropriate comparison data from storage 50 based on the food group of the identified food and compares the result to the comparison data to produce the relative healthfulness data. Processor 44 then controls presentation device 60 to display the relative healthfulness data to the consumer.

In certain ones of such embodiments, storage 50 stores relative healthfulness data for a plurality of predetermined foods, which can be retrieved using an address based on an identification of the food input by the consumer using input 56. Processor 44 produces an address for the corresponding relative healthfulness data in storage 50 and reads the relative healthfulness data therefrom using the address. Processor 44 then controls presentation device 60 to display the relative healthfulness data to the consumer.

In certain ones of such embodiments, the relative healthfulness data stored in storage 50 is downloaded from a server via a network. With reference to FIG. 13, in certain embodiments a plurality of data processing systems 40′ and 40″, each corresponding to data processing system 40 access a server 76 via a network 70 to obtain the relative healthfulness data, either to obtain a database of food energy data or to update such a database stored in their storage 50. Network 70 may be a LAN, WAN, metropolitan area network or an internetwork, such as the Internet. Server 76 stores relative healthfulness data for a large number and variety of foods and candidate food servings which have been produced thereby, obtained from another host on network 70 or a different network, or input from a removable storage device or via an input of server 76 (not shown for purposes of simplicity and clarity).

In certain ones of such embodiments, processor 44 of one of data processing systems 40′ and 40″ receives the input data from input 56 and the consumer, and controls communications 64 to communicate such data to server 76 via network 70. Server 76 either retrieves the corresponding relative healthfulness data from a storage thereof (not shown for purposes of simplicity and clarity), or produces the relative healthfulness data from the received data using the process identified by the food group identification data, as appropriate, and communicates the relative healthfulness data to communications 64. Processor 44 then controls presentation device 60 to display the relative healthfulness data to the consumer.

The systems of FIGS. 12 and 13 are configured in certain embodiments to produce meal plan data for a person on request. A meal plan for a given person is based on a personal profile of the person and relative healthfulness data produced for a variety of foods, either prior to the request for the meal plan data or upon such request. The personal profile includes such data as may be necessary to retrieve or produce a meal plan tailored to the needs and/or desires of the requesting person, and can include data such as the person's weight, height, body fat, gender, age, attitude, physical activity level, weight goals, race, religion, ethnicity, health restrictions and needs, such as diseases and injuries, and consequent dietary restrictions and needs. This data is entered by the requesting person via input 56 of the system 40 in FIG. 12, and stored as a personal profile either by processor 44 in storage 50, or communicated by communications 64 to be stored by server 76.

In certain embodiments, processor 44 accesses appropriate instructions from storage 50 to produce a plurality of meal plans each designed to fulfill predetermined criteria, such as a low-fat diet, a low carbohydrate diet, an ethnically or religiously appropriate diet, or the like. Criteria and methods for producing such diets are well known and encompass the criteria and methods disclosed by US published patent application No. 2004/0171925, published Sep. 2, 2004 in the names of David Kirchoff, et al. and assigned to the assignee of the present application. US 2004/0171925 is hereby incorporated by reference herein in its entirety.

Processor 44 also obtains healthfulness data produced as described herein above for the various foods in or to be included in the meal plan data, and selects and/or substitutes foods for the meal plan based on the healthfulness data. In certain ones of such embodiments, processor 44 selects and/or substitutes the foods in order to maximize the healthfulness of the foods in the meal plan data overall based on their relative healthfulness data. In certain ones of such embodiments, processor 44 selects and/or substitutes the foods in order to achieve a minimum target level of healthfulness of the foods in the meal plan data based on their relative healthfulness data. In certain ones of such embodiments, the processor 44 produces meal plan data matched to predetermined criteria and stores the data in storage 50 for subsequent access upon a request for meal plan data. Upon receipt of such a request, processor 44 accesses the meal plan data based on a requesters profile data presents it to the requester via presentation device 60.

Once the meal plan data is been thus produced, processor 44 controls presentation device 60 to present the meal plan data to the requesting person. In certain embodiments in which the server 76 obtains the meal plan data, server 76 communicates the meal plan data to communications 64 for presentation to the requesting person via presentation device 60. In certain ones of such embodiments, the server 76 produces meal plan data matched to predetermined criteria and stores the data for subsequent access upon a request for meal plan data. Upon receipt of such a request from one of systems 40′ and 40″, server 76 accesses the meal plan data based on a requester's profile data and communicates it to the requesting system for presentation to the requester.

Consumers often are confused by the extensive nutritional information printed on the packaging of foods. Some simply find it too burdensome to read such information, often in relatively fine print so that it can all fit in the available space, and then weigh the relative merits and undesirable aspects of such information. While the Traffic Light system provides a degree of simplification to this process, it is still necessary for the consumer to look for additional information on the packaging in order to acquire information desired by those attempting to maintain, lose or gain weight.

In certain embodiments, an integrated image associated with a candidate for serving or food offered for sale simplifies the task of evaluating the desirability of the food based both on its energy content and relative healthfulness.

When the consumer considers whether to ingest a candidate food serving or purchase a food offered for sale, the consumer views an integrated image including both a numeral representing an energy value of the food serving and a further image feature representing its relative healthfulness. In certain advantageous embodiments, such relative healthfulness is represented by distinctly different and suggestive image colors, shades, shapes, brightness, or textures.

The integrated image may be imprinted on the packaging or label of the candidate food serving or food offered for sale, or it may be displayed by a data processing system, such as a PDA, cellular telephone, laptop computer or desktop computer, as described more fully hereinbelow. It may also be displayed in a printed document.

The integrated image in certain embodiments comprises a numeral representing the energy content of an associated food displayed on a background colored to represent a further nutritional quality of the candidate food serving. An example of such an integrated image is provided in FIG. 14A wherein the numeral comprises an integer on a green background with a triangular border.

A further example of such an integrated image is provided in FIG. 14B wherein the numeral comprises a different integer within a circular border. The shape of the border may be used by itself to represent relative healthfulness, while the numeral represents food energy data. In other embodiments, both the shape of the border and a color, shading or texture enclosed by the border can provide the data for the healthfulness characteristic represented by the shape in FIG. 14B.

Still another example of an integrated image is provided in FIG. 14C wherein the numeral 6.5 appears within the image to provide food energy data, and the rectangular border of the image, with or without a color, shading or texture code, to provide the data for the relative healthfulness of the food.

FIG. 14D illustrates a still further integrated image in which a numeral representing an energy content of a candidate food serving is colored to represent the relative healthfulness of the candidate food serving or food offered for sale. While the numeral of FIG. 14D is not enclosed within a border, in certain embodiments a border is provided. In still other embodiments, the numeral is shaded or textured to provide the data for the relative healthfulness. Various other shapes may also be used, such as a star, oval or donut shape. Any shapes, colors, textures and shadings may be used, whether alone or in combination to provide the data for relative healthfulness of the food. Moreover, arabic numerals need not be used, so that any data representing numerical data (such as roman numerals) can serve as the numeral data to represent energy content.

FIG. 15 is a flow chart used to illustrate certain embodiments of a process for producing a food product having relative healthfulness data associated therewith. A food product is obtained 300, whether by producing the food product, by retrieving it from inventory or receiving a delivery thereof. Accordingly, the food product may be a processed food product, or it may be a raw food product, such as an agricultural product or seafood.

At least one of food identification data and food nutrient data of the food product is supplied 310. The food identification data may be the name of the food, a stock keeping unit or other data as described hereinbelow. Healthfulness data representing a relative healthfulness of the food product is obtained 320 based on the food identification data or the food nutrient data, using one of the processes disclosed hereinabove. In certain ones of such embodiments, the food identification data is input to a data processing system storing healthfulness data for one or more food products. In this example, the food identification data may be a name of the food product, an identifier such as a stock keeping unit, or data which associates the food product with its respective stored healthfulness data. In certain ones of such embodiments, such food nutrient data is supplied to a data processing system as may be required to produce healthfulness data for the food product using one of the processes disclosed hereinabove. In certain ones of such embodiments, the healthfulness data is obtained from an appropriate record or calculated in accordance with one of the processes disclosed hereinabove.

The healthfulness data obtained as disclosed hereinabove is associated 330 with the food product. In certain ones of such embodiments, the healthfulness data is printed, applied or otherwise made visible on packaging of the food product. In certain ones of such embodiments, the healthfulness data is made visible on a label affixed on or to the food product, such as an adhesive-backed label on produce or a label tethered to a food product.

The foregoing disclosure of certain embodiments provides exemplary ways of implementing the principles of the present invention, and the scope of the invention is not limited by this disclosure. This invention can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete to those skilled in the art. The scope of the present invention is instead defined by the following claims. 

1. A process for selecting and consuming and/or purchasing food based on the healthfulness of the food relative to one or more other foods, comprising, for each of a plurality of candidate foods, obtaining respective healthfulness data representing a relative healthfulness of each of the candidate foods, the relative healthfulness data based on a linear combination of selected nutrient amounts present therein; selecting at least one of the candidate foods from the plurality of candidate foods based on its respective healthfulness data; and at least one of ingesting the at least one of the candidate foods and purchasing the at least one of the candidate foods.
 2. The process of claim 1, comprising obtaining relative healthfulness data for at least one of the candidate foods based on a linear combination of the selected nutrient amounts thereof and an energy density thereof.
 3. The process of claim 1, comprising obtaining relative healthfulness data for at least two of the candidate foods based on a respectively different linear combination of selected nutrient amounts therein.
 4. The process of claim 1, wherein each of the candidate foods is classified in a respective one of a plurality of food groups, and the healthfulness data of each of the candidate foods is based on a respective linear combination of selected nutrients therein corresponding to the food group thereof, the respective linear combinations of selected nutrients of at least two of the food groups being different.
 5. The process of claim 1, comprising obtaining meal plan data comprising data identifying food servings to be ingested over a given period based on the healthfulness data, and the at least one of the candidate foods is selected based on the meal plan data.
 6. The process of claim 1, comprising ingesting the at least one of the candidate foods.
 7. The process of claim 1, comprising purchasing the at least one of the candidate foods.
 8. A process for producing relative healthfulness data for a selected food, comprising, in a data processing system, receiving a plurality of nutrient data representing amounts of each of a plurality of nutrients in the selected food; and in the data processing system, obtaining relative healthfulness data for the selected food based on a linear combination of the plurality of nutrient data.
 9. The process of claim 8, comprising obtaining relative healthfulness data for the selected food based on a linear combination of the plurality of nutrient data and an energy density of the selected food.
 10. The process of claim 8, wherein a storage of the data processing system stores instructions for linearly combining a plurality of nutrient data of foods within a plurality of food groups, the instructions for at least some of the plurality of foods groups differing from others thereof, comprising obtaining the healthfulness data of the selected food by accessing respective instructions for a food group thereof from the storage using a processor of the data processing system and, using the processor, linearly combining the plurality of nutrients of the selected food by executing the respective instructions.
 11. The process of claim 8, comprising obtaining the healthfulness data of the selected food by accessing the healthfulness data from a storage of the data processing system.
 12. The process of claim 8, comprising storing the relative healthfulness data for the selected food in a storage of the data processing system to update a database of relative healthfulness data.
 13. A process for providing data to a data requester representing healthfulness of a predetermined food relative to one or more other foods, comprising, receiving in a data processing system request data provided by the data requestor requesting relative healthfulness data for a selected food; using a processor of the data processing system, obtaining relative healthfulness data representing a relative healthfulness of the selected food, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; and at least one of (a) communicating the relative healthfulness data to a device for presentation to the consumer, and (b) presenting the relative healthfulness data to the consumer via a presentation device of the data processing system.
 14. The process of claim 13, comprising obtaining relative healthfulness data for the selected food based on a linear combination of the selected nutrient amounts and an energy density of the selected food.
 15. The process of claim 13, wherein a storage of the data processing system stores instructions for linearly combining a plurality of nutrient amounts of foods within a plurality of food groups, the instructions for at least some of the plurality of foods groups differing from others thereof, comprising obtaining the relative healthfulness data of the selected food by accessing respective instructions for a food group thereof from the storage using the processor of the data processing system and, using the processor, linearly combining the selected nutrient amounts of the selected food by executing the respective instructions.
 16. The process of claim 13, comprising obtaining the relative healthfulness data of the selected food by accessing the relative healthfulness data from a storage of the data processing system.
 17. A system for providing data to a data requester representing healthfulness of a selected food relative to one or more other foods, comprising, an input operative to receive request data provided by the data requestor requesting relative healthfulness data for a selected food; a processor coupled with the input to receive the request data provided by the data requester and configured to obtain relative healthfulness data representing a relative healthfulness of the selected food, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; and at least one of (a) communications coupled with the processor to receive the relative healthfulness data therefrom and to communicate the relative healthfulness data to a device for presentation to the consumer, and (b) a presentation device coupled with the processor to receive the relative healthfulness data and operative to present the relative healthfulness data to the consumer.
 18. The system of claim 17, wherein the processor is configured to obtain the relative healthfulness data of the selected food based on a linear combination of the selected nutrient amounts and an energy density of the selected food.
 19. The system of claim 17, comprising a storage coupled with the processor and storing instructions for linearly combining a plurality of nutrient amounts of foods within a plurality of food groups, the instructions for at least some of the plurality of foods groups differing from others thereof, the processor being configured to obtain the healthfulness data of the selected food by accessing respective instructions for a food group thereof from the storage and to linearly combine the selected nutrient amounts of the selected food by executing the respective instructions.
 20. The system of claim 17, comprising a storage coupled with the processor and storing the relative healthfulness data, the processor being configured to obtain the relative healthfulness data of the selected food by accessing the relative healthfulness data from the storage.
 21. The system of claim 17, comprising communications coupled with the processor to receive the relative healthfulness data therefrom and to communicate the relative healthfulness data to a device for presentation to the consumer.
 22. The system of claim 17, comprising a presentation device coupled with the processor to receive the relative healthfulness data and operative to present the relative healthfulness data to the consumer.
 23. A process for providing meal plan data to a consumer, comprising, receiving request data in a data processing system representing a request for a meal plan from a consumer; in response to the request, obtaining meal plan data representing a plurality of predetermined food servings to be consumed by the consumer during a predetermined period, the meal plan data being based on relative healthfulness data for the respective predetermined food servings, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; and at least one of (a) communicating the meal plan data to a device for presentation to the data requester, and (b) presenting the meal plan data to the data requester via a presentation device of the data processing system.
 24. The process of claim 23, comprising obtaining the relative healthfulness data based on the linear combination of selected nutrient amounts present in the respective predetermined food servings.
 25. The process of claim 24, comprising obtaining the relative healthfulness data for the respective predetermined food servings based on a linear combination of selected nutrient amounts present therein and an energy density thereof.
 26. The process of claim 24, wherein a storage of the data processing system stores instructions for linearly combining selected nutrient amounts present in respective predetermined food servings within a plurality of food groups, the instructions for at least some of the plurality of foods groups differing from others thereof, comprising obtaining the relative healthfulness data of the respective predetermined food servings by accessing respective instructions for a food group thereof from the storage using the processor of the data processing system and, using the processor, linearly combining the selected nutrient amounts of the respective predetermined food servings by executing the respective instructions.
 27. The process of claim 24, comprising obtaining the relative healthfulness data of the respective predetermined food servings by accessing the relative healthfulness data from a storage of the data processing system.
 28. The process of claim 23, comprising obtaining the meal plan data by accessing the meal plan data from a storage of the data processing system.
 29. The process of claim 23, comprising communicating the meal plan data to a device for presentation to the data requester.
 30. The process of claim 23, comprising presenting the meal plan data to the data requester via a presentation device of the data processing system.
 31. A system for providing meal plan data to a consumer, comprising, an input operative to receive request data representing a request for a meal plan from the consumer; a processor coupled with the input to receive the request data and configured to obtain meal plan data representing a plurality of predetermined food servings to be consumed by the consumer during a predetermined period, the meal plan data being based on relative healthfulness data for each of a plurality of predetermined food servings, the relative healthfulness data being based on a linear combination of selected nutrient amounts present therein; and at least one of (a) communications coupled with the processor to receive the meal plan data therefrom and to communicate the meal plan data to a device for presentation to the consumer, and (b) a presentation device coupled with the processor to receive the meal plan data and operative to present the meal plan data to the consumer.
 32. The system of claim 31, wherein the processor is configured to obtain the relative healthfulness data based on the linear combination of selected nutrient amounts.
 33. The system of claim 32, wherein the processor is configured to obtain relative healthfulness data for the respective predetermined food servings based on a linear combination of selected nutrient amounts present therein and an energy density thereof.
 34. The system of claim 32, comprising a storage coupled with the processor and storing instructions for linearly combining selected nutrient amounts present in respective predetermined food servings within a plurality of food groups, the instructions for at least some of the plurality of foods groups differing from others thereof, wherein the processor is configured to obtain the relative healthfulness data of the respective predetermined food servings by accessing respective instructions for a food group thereof from the storage and to linearly combine the selected nutrient amounts of the respective predetermined food servings by executing the respective instructions.
 35. The system of claim 32, comprising a storage coupled with the processor and storing relative healthfulness data for the respective predetermined food servings, wherein the processor is configured to access the relative healthfulness data from the storage.
 36. The system of claim 31, comprising a storage coupled with the processor and storing the meal plan data, wherein the processor is configured to access the meal plan data from the storage.
 37. The system of claim 31, comprising communications coupled with the processor to receive the meal plan data therefrom and to communicate the meal plan data to a device for presentation to the consumer.
 38. The system of claim 31, comprising a presentation device coupled with the processor to receive the meal plan data and operative to present the meal plan data to the consumer.
 39. A process for producing a food product having relative healthfulness data associated therewith, comprising, obtaining a food product, supplying at least one of food identification data and food nutrient data of the food product; obtaining healthfulness data representing a relative healthfulness of the food product based on its at least one of food identification data and food nutrient data, the healthfulness data for the food product being based on a linear combination of selected nutrient amounts present therein; and associating the healthfulness data with the food product.
 40. The process of claim 39, wherein obtaining the food product comprises producing the food product.
 41. The process of claim 39, wherein the healthfulness data is associated with the food product by including the healthfulness data on a substrate associated with the food product.
 42. The process of claim 41, wherein the substrate comprises a label accompanying the food product.
 43. The process of claim 41, wherein the substrate comprises packaging of the food product. 